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Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04-6.06, 7.02-7.03, and 10.06-10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%).

We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized.
We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8 that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7 to a conventional model 9. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.

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Trajectory Data Analyses for Pedestrian Space-time Activity Study

Authors: Feng Qi, Fei Du.

Institutions: Kean University, University of Wisconsin-Madison.

It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4.
Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling.
The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5 involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6 and density volume rendering7. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

KCNE genes encode for a small family of Kv channel ancillary subunits that form heteromeric complexes with Kv channel alpha subunits to modify their functional properties. Mutations in KCNE genes have been found in patients with cardiac arrhythmias such as the long QT syndrome and/or atrial fibrillation. However, the precise molecular pathophysiology that leads to these diseases remains elusive. In previous studies the electrophysiological properties of the disease causing mutations in these genes have mostly been studied in heterologous expression systems and we cannot be sure if the reported effects can directly be translated into native cardiomyocytes. In our laboratory we therefore use a different approach. We directly study the effects of KCNE gene deletion in isolated cardiomyocytes from knockout mice by cellular electrophysiology - a unique technique that we describe in this issue of the Journal of Visualized Experiments. The hearts from genetically engineered KCNE mice are rapidly excised and mounted onto a Langendorff apparatus by aortic cannulation. Free Ca2+ in the myocardium is bound by EGTA, and dissociation of cardiac myocytes is then achieved by retrograde perfusion of the coronary arteries with a specialized low Ca2+ buffer containing collagenase. Atria, free right ventricular wall and the left ventricle can then be separated by microsurgical techniques. Calcium is then slowly added back to isolated cardiomyocytes in a multiple step comprising washing procedure. Atrial and ventricular cardiomyocytes of healthy appearance with no spontaneous contractions are then immediately subjected to electrophysiological analyses by patch clamp technique or other biochemical analyses within the first 6 hours following isolation.

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Authors: Bianca DeBenedictis, J. Bruce Morton.

Institutions: University of Western Ontario.

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.

A Rapid and Efficient Method for Assessing Pathogenicity of Ustilago maydis on Maize and Teosinte Lines

Authors: Suchitra Chavan, Shavannor M. Smith.

Institutions: University of Georgia.

Maize is a major cereal crop worldwide. However, susceptibility to biotrophic pathogens is the primary constraint to increasing productivity. U. maydis is a biotrophic fungal pathogen and the causal agent of corn smut on maize. This disease is responsible for significant yield losses of approximately $1.0 billion annually in the U.S.1 Several methods including crop rotation, fungicide application and seed treatments are currently used to control corn smut2. However, host resistance is the only practical method for managing corn smut. Identification of crop plants including maize, wheat, and rice that are resistant to various biotrophic pathogens has significantly decreased yield losses annually3-5. Therefore, the use of a pathogen inoculation method that efficiently and reproducibly delivers the pathogen in between the plant leaves, would facilitate the rapid identification of maize lines that are resistant to U. maydis. As, a first step toward indentifying maize lines that are resistant to U. maydis, a needle injection inoculation method and a resistance reaction screening method was utilized to inoculate maize, teosinte, and maize x teosinte introgression lines with a U. maydis strain and to select resistant plants.
Maize, teosinte and maize x teosinte introgression lines, consisting of about 700 plants, were planted, inoculated with a strain of U. maydis, and screened for resistance. The inoculation and screening methods successfully identified three teosinte lines resistant to U. maydis. Here a detailed needle injection inoculation and resistance reaction screening protocol for maize, teosinte, and maize x teosinte introgression lines is presented. This study demonstrates that needle injection inoculation is an invaluable tool in agriculture that can efficiently deliver U. maydis in between the plant leaves and has provided plant lines that are resistant to U. maydis that can now be combined and tested in breeding programs for improved disease resistance.

Microinjecting DNA into the cytoplasm of the syncytial gonad of Caenorhabditis elegans is the main technique used to establish transgenic lines that exhibit partial and variable transmission rates of extrachromosomal arrays to the next generation. In addition, transgenic animals are mosaic and express the transgene in a variable number of cells. Extrachromosomal arrays can be integrated into the C. elegans genome using UV irradiation to establish nonmosaic transgenic strains with 100% transmission rate of the transgene. To that extent, F1 progenies of UV irradiated transgenic animals are screened for animals carrying a heterozygous integration of the transgene, which leads to a 75% Mendelian transmission rate to the F2 progeny. One of the challenges of this method is to distinguish between the percentage of transgene transmission in a population before (X% transgenic animals) and after integration (≥75% transgenic F2 animals). Thus, this method requires choosing a nonintegrated transgenic line with a percentage of transgenic animals that is significantly lower than the Mendelian segregation of 75%. Consequently, nonintegrated transgenic lines with an extrachromosomal array transmission rate to the next generation ≤60% are usually preferred for integration, and transgene integration in highly transmitting strains is difficult. Here we show that the efficiency of extrachromosomal arrays integration into the genome is increased when using highly transmitting transgenic lines (≥80%). The described protocol allows for easy selection of several independent lines with homozygous transgene integration into the genome after UV irradiation of transgenic worms exhibiting a high rate of extrachromosomal array transmission. Furthermore, this method is quite fast and low material consuming. The possibility of rapidly generating different lines that express a particular integrated transgene is of great interest for studies focusing on gene expression pattern and regulation, protein localization, and overexpression, as well as for the development of subcellular markers.

Targeted genetic manipulation using homologous recombination is the method of choice for functional genomic analysis to obtain a detailed view of gene function and phenotype(s). The development of mutant strains with targeted gene deletions, targeted mutations, complemented gene function, and/or tagged genes provides powerful strategies to address gene function, particularly if these genetic manipulations can be efficiently targeted to the gene locus of interest using integration mediated by double cross over homologous recombination.
Due to very high rates of nonhomologous recombination, functional genomic analysis of Toxoplasma gondii has been previously limited by the absence of efficient methods for targeting gene deletions and gene replacements to specific genetic loci. Recently, we abolished the major pathway of nonhomologous recombination in type I and type II strains of T. gondii by deleting the gene encoding the KU80 protein1,2. The Δku80 strains behave normally during tachyzoite (acute) and bradyzoite (chronic) stages in vitro and in vivo and exhibit essentially a 100% frequency of homologous recombination. The Δku80 strains make functional genomic studies feasible on the single gene as well as on the genome scale1-4.
Here, we report methods for using type I and type II Δku80Δhxgprt strains to advance gene targeting approaches in T. gondii. We outline efficient methods for generating gene deletions, gene replacements, and tagged genes by targeted insertion or deletion of the hypoxanthine-xanthine-guanine phosphoribosyltransferase (HXGPRT) selectable marker. The described gene targeting protocol can be used in a variety of ways in Δku80 strains to advance functional analysis of the parasite genome and to develop single strains that carry multiple targeted genetic manipulations. The application of this genetic method and subsequent phenotypic assays will reveal fundamental and unique aspects of the biology of T. gondii and related significant human pathogens that cause malaria (Plasmodium sp.) and cryptosporidiosis (Cryptosporidium).

The zebrafish has become a mainstream vertebrate model that is relevant for many disciplines of scientific study. Zebrafish are especially well suited for forward genetic analysis of developmental processes due to their external fertilization, embryonic size, rapid ontogeny, and optical clarity – a constellation of traits that enable the direct observation of events ranging from gastrulation to organogenesis with a basic stereomicroscope. Further, zebrafish embryos can survive for several days in the haploid state. The production of haploid embryos in vitro is a powerful tool for mutational analysis, as it enables the identification of recessive mutant alleles present in first generation (F1) female carriers following mutagenesis in the parental (P) generation. This approach eliminates the necessity to raise multiple generations (F2, F3, etc.) which involves breeding of mutant families, thus saving the researcher time along with reducing the needs for zebrafish colony space, labor, and the husbandry costs. Although zebrafish have been used to conduct forward screens for the past several decades, there has been a steady expansion of transgenic and genome editing tools. These tools now offer a plethora of ways to create nuanced assays for next generation screens that can be used to further dissect the gene regulatory networks that drive vertebrate ontogeny. Here, we describe how to prepare haploid zebrafish embryos. This protocol can be implemented for novel future haploid screens, such as in enhancer and suppressor screens, to address the mechanisms of development for a broad number of processes and tissues that form during early embryonic stages.

In Situ Hybridization for the Precise Localization of Transcripts in Plants

Authors: Marie Javelle, Cristina F. Marco, Marja Timmermans.

Institutions: Cold Spring Harbor Laboratory.

With the advances in genomics research of the past decade, plant biology has seen numerous studies presenting large-scale quantitative analyses of gene expression. Microarray and next generation sequencing approaches are being used to investigate developmental, physiological and stress response processes, dissect epigenetic and small RNA pathways, and build large gene regulatory networks1-3. While these techniques facilitate the simultaneous analysis of large gene sets, they typically provide a very limited spatiotemporal resolution of gene expression changes. This limitation can be partially overcome by using either profiling method in conjunction with lasermicrodissection or fluorescence-activated cell sorting4-7. However, to fully understand the biological role of a gene, knowledge of its spatiotemporal pattern of expression at a cellular resolution is essential. Particularly, when studying development or the effects of environmental stimuli and mutants can the detailed analysis of a gene's expression pattern become essential. For instance, subtle quantitative differences in the expression levels of key regulatory genes can lead to dramatic phenotypes when associated with the loss or gain of expression in specific cell types.
Several methods are routinely used for the detailed examination of gene expression patterns. One is through analysis of transgenic reporter lines. Such analysis can, however, become time-consuming when analyzing multiple genes or working in plants recalcitrant to transformation. Moreover, an independent validation to ensure that the transgene expression pattern mimics that of the endogenous gene is typically required. Immunohistochemical protein localization or mRNA in situ hybridization present relatively fast alternatives for the direct visualization of gene expression within cells and tissues. The latter has the distinct advantage that it can be readily used on any gene of interest. In situ hybridization allows detection of target mRNAs in cells by hybridization with a labeled anti-sense RNA probe obtained by in vitro transcription of the gene of interest.
Here we outline a protocol for the in situ localization of gene expression in plants that is highly sensitivity and specific. It is optimized for use with paraformaldehyde fixed, paraffin-embedded sections, which give excellent preservation of histology, and DIG-labeled probes that are visualized by immuno-detection and alkaline-phosphatase colorimetric reaction. This protocol has been successfully applied to a number of tissues from a wide range of plant species, and can be used to analyze expression of mRNAs as well as small RNAs8-14.

The scaling of body parts is a central feature of animal morphology1-7. Within species, morphological traits need to be correctly proportioned to the body for the organism to function; larger individuals typically have larger body parts and smaller individuals generally have smaller body parts, such that overall body shape is maintained across a range of adult body sizes. The requirement for correct proportions means that individuals within species usually exhibit low variation in relative trait size. In contrast, relative trait size can vary dramatically among species and is a primary mechanism by which morphological diversity is produced. Over a century of comparative work has established these intra- and interspecific patterns3,4.
Perhaps the most widely used approach to describe this variation is to calculate the scaling relationship between the size of two morphological traits using the allometric equation y=bxα, where x and y are the size of the two traits, such as organ and body size8,9. This equation describes the within-group (e.g., species, population) scaling relationship between two traits as both vary in size. Log-transformation of this equation produces a simple linear equation, log(y) = log(b) + αlog(x) and log-log plots of the size of different traits among individuals of the same species typically reveal linear scaling with an intercept of log(b) and a slope of α, called the 'allometric coefficient'9,10. Morphological variation among groups is described by differences in scaling relationship intercepts or slopes for a given trait pair. Consequently, variation in the parameters of the allometric equation (b and α) elegantly describes the shape variation captured in the relationship between organ and body size within and among biological groups (see 11,12).
Not all traits scale linearly with each other or with body size (e.g., 13,14) Hence, morphological scaling relationships are most informative when the data are taken from the full range of trait sizes. Here we describe how simple experimental manipulation of diet can be used to produce the full range of body size in insects. This permits an estimation of the full scaling relationship for any given pair of traits, allowing a complete description of how shape covaries with size and a robust comparison of scaling relationship parameters among biological groups. Although we focus on Drosophila, our methodology should be applicable to nearly any fully metamorphic insect.

Institutions: University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, Emory University School of Medicine, University of North Carolina School of Medicine.

Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

Institutions: University of Arizona, Michigan State University, The Institute for Advanced Learning and Research, Michigan State University.

To facilitate the use of lignocellulosic biomass as an alternative bioenergy resource, during biological conversion processes, a pretreatment step is needed to open up the structure of the plant cell wall, increasing the accessibility of the cell wall carbohydrates. Lignin, a polyphenolic material present in many cell wall types, is known to be a significant hindrance to enzyme access. Reduction in lignin content to a level that does not interfere with the structural integrity and defense system of the plant might be a valuable step to reduce the costs of bioethanol production. In this study, we have genetically down-regulated one of the lignin biosynthesis-related genes, cinnamoyl-CoA reductase (ZmCCR1) via a double stranded RNA interference technique. The ZmCCR1_RNAi construct was integrated into the maize genome using the particle bombardment method. Transgenic maize plants grew normally as compared to the wild-type control plants without interfering with biomass growth or defense mechanisms, with the exception of displaying of brown-coloration in transgenic plants leaf mid-ribs, husks, and stems. The microscopic analyses, in conjunction with the histological assay, revealed that the leaf sclerenchyma fibers were thinned but the structure and size of other major vascular system components was not altered. The lignin content in the transgenic maize was reduced by 7-8.7%, the crystalline cellulose content was increased in response to lignin reduction, and hemicelluloses remained unchanged. The analyses may indicate that carbon flow might have been shifted from lignin biosynthesis to cellulose biosynthesis. This article delineates the procedures used to down-regulate the lignin content in maize via RNAi technology, and the cell wall compositional analyses used to verify the effect of the modifications on the cell wall structure.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

The rotting of grains by seed-infecting fungi poses one of the greatest economic challenges to cereal production worldwide, not to mention serious risks to human and animal health. Among cereal production, maize is arguably the most affected crop, due to pathogen-induced losses in grain integrity and mycotoxin seed contamination. The two most prevalent and problematic mycotoxins for maize growers and food and feed processors are aflatoxin and fumonisin, produced by Aspergillus flavus and Fusarium verticillioides, respectively.
Recent studies in molecular plant-pathogen interactions have demonstrated promise in understanding specific mechanisms associated with plant responses to fungal infection and mycotoxin contamination1,2,3,4,5,6. Because many labs are using kernel assays to study plant-pathogen interactions, there is a need for a standardized method for quantifying different biological parameters, so results from different laboratories can be cross-interpreted. For a robust and reproducible means for quantitative analyses on seeds, we have developed in-lab kernel assays and subsequent methods to quantify fungal growth, biomass, and mycotoxin contamination. Four sterilized maize kernels are inoculated in glass vials with a fungal suspension (106) and incubated for a predetermined period. Sample vials are then selected for enumeration of conidia by hemocytometer, ergosterol-based biomass analysis by high performance liquid chromatography (HPLC), aflatoxin quantification using an AflaTest fluorometer method, and fumonisin quantification by HPLC.

Institutions: University of Toronto, University of Toronto, University of Regina.

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10.
Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Authors: Marcus Cheetham, Lutz Jancke.

Institutions: University of Zurich.

Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.

A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research

Authors: Brian H. Smith, Christina M. Burden.

Institutions: Arizona State University.

Insects modify their responses to stimuli through experience of associating those stimuli with events important for survival (e.g., food, mates, threats). There are several behavioral mechanisms through which an insect learns salient associations and relates them to these events. It is important to understand this behavioral plasticity for programs aimed toward assisting insects that are beneficial for agriculture. This understanding can also be used for discovering solutions to biomedical and agricultural problems created by insects that act as disease vectors and pests. The Proboscis Extension Response (PER) conditioning protocol was developed for honey bees (Apis mellifera) over 50 years ago to study how they perceive and learn about floral odors, which signal the nectar and pollen resources a colony needs for survival. The PER procedure provides a robust and easy-to-employ framework for studying several different ecologically relevant mechanisms of behavioral plasticity. It is easily adaptable for use with several other insect species and other behavioral reflexes. These protocols can be readily employed in conjunction with various means for monitoring neural activity in the CNS via electrophysiology or bioimaging, or for manipulating targeted neuromodulatory pathways. It is a robust assay for rapidly detecting sub-lethal effects on behavior caused by environmental stressors, toxins or pesticides.
We show how the PER protocol is straightforward to implement using two procedures. One is suitable as a laboratory exercise for students or for quick assays of the effect of an experimental treatment. The other provides more thorough control of variables, which is important for studies of behavioral conditioning. We show how several measures for the behavioral response ranging from binary yes/no to more continuous variable like latency and duration of proboscis extension can be used to test hypotheses. And, we discuss some pitfalls that researchers commonly encounter when they use the procedure for the first time.

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.

Institutions: University of Alberta, University of Alberta, University of Illinois, Duke University , Duke University , VA Medical Center, Yale University, University of Illinois, University of Illinois.

Emotions can impact cognition by exerting both enhancing (e.g., better memory for emotional events) and impairing (e.g., increased emotional distractibility) effects (reviewed in 1). Complementing our recent protocol 2 describing a method that allows investigation of the neural correlates of the memory-enhancing effect of emotion (see also 1, 3-5), here we present a protocol that allows investigation of the neural correlates of the detrimental impact of emotion on cognition. The main feature of this method is that it allows identification of reciprocal modulations between activity in a ventral neural system, involved in 'hot' emotion processing (HotEmo system), and a dorsal system, involved in higher-level 'cold' cognitive/executive processing (ColdEx system), which are linked to cognitive performance and to individual variations in behavior (reviewed in 1). Since its initial introduction 6, this design has proven particularly versatile and influential in the elucidation of various aspects concerning the neural correlates of the detrimental impact of emotional distraction on cognition, with a focus on working memory (WM), and of coping with such distraction 7,11, in both healthy 8-11 and clinical participants 12-14.

Institutions: University of Illinois, Urbana-Champaign, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign.

The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress has been made in understanding conscious/deliberate emotion regulation (ER), less is known about non-conscious/automatic ER and the associated neural correlates. This is in part due to the problems inherent in the unitary concepts of automatic and conscious processing1. Here, we present a protocol that allows investigation of the neural correlates of both deliberate and automatic ER using functional magnetic resonance imaging (fMRI). This protocol allows new avenues of inquiry into various aspects of ER. For instance, the experimental design allows manipulation of the goal to regulate emotion (conscious vs. non-conscious), as well as the intensity of the emotional challenge (high vs. low). Moreover, it allows investigation of both immediate (emotion perception) and long-term effects (emotional memory) of ER strategies on emotion processing. Therefore, this protocol may contribute to better understanding of the neural mechanisms of emotion regulation in healthy behaviour, and to gaining insight into possible causes of deficits in depression and anxiety disorders in which emotion dysregulation is often among the core debilitating features.

Institutions: University of Alberta, University of Illinois, Urbana-Champaign, Duke University, University of Illinois, Urbana-Champaign.

Emotional events tend to be better remembered than non-emotional events1,2. One goal of cognitive and affective neuroscientists is
to understand the neural mechanisms underlying this enhancing effect of emotion on memory. A method that has proven particularly influential in the
investigation of the memory-enhancing effect of emotion is the so-called subsequent memory paradigm (SMP). This method was originally used to investigate the
neural correlates of non-emotional memories3, and more recently we and others also applied it successfully to studies of emotional memory (reviewed in4, 5-7).
Here, we describe a protocol that allows investigation of the neural correlates of the memory-enhancing effect of emotion using the SMP in conjunction with
event-related functional magnetic resonance imaging (fMRI). An important feature of the SMP is that it allows separation of brain activity specifically
associated with memory from more general activity associated with perception. Moreover, in the context of investigating the impact of emotional stimuli,
SMP allows identification of brain regions whose activity is susceptible to emotional modulation of both general/perceptual and memory-specific processing.
This protocol can be used in healthy subjects8-15, as well as in clinical patients where there are alterations in the neural correlates of emotion perception
and biases in remembering emotional events, such as those suffering from depression and post-traumatic stress disorder (PTSD)16, 17.

Caroli's disease is defined as a abnormal dilatation of the intra-hepatica bile ducts: Its incidence is extremely low (1 in 1,000,000 population) and in most of the cases the whole liver is interested and liver transplantation is the treatment of choice. In case of dilatation limited to the left or right lobe, liver resection can be performed. For many year the standard approach for liver resection has been a formal laparotomy by means of a large incision of abdomen that is characterized by significant post-operatie morbidity. More recently, minimally invasive, laparoscopic approach has been proposed as possible surgical technique for liver resection both for benign and malignant diseases. The main benefits of the minimally invasive approach is represented by a significant reduction of the surgical trauma that allows a faster recovery a less post-operative complications.
This video shows a case of Caroli s disease occured in a 58 years old male admitted at the gastroenterology department for sudden onset of abdominal pain associated with fever (>38C° ), nausea and shivering. Abdominal ultrasound demonstrated a significant dilatation of intra-hepatic left sited bile ducts with no evidences of gallbladder or common bile duct stones. Such findings were confirmed abdominal high resolution computer tomography.
Laparoscopic left sectoriectomy was planned. Five trocars and 30° optic was used, exploration of the abdominal cavity showed no adhesions or evidences of other diseases.
In order to control blood inflow to the liver, vascular clamp was placed on the hepatic pedicle (Pringle s manouvre), Parenchymal division is carried out with a combined use of 5 mm bipolar forceps and 5 mm ultrasonic dissector. A severely dilated left hepatic duct was isolated and divided using a 45mm endoscopic vascular stapler. Liver dissection was continued up to isolation of the main left portal branch that was then divided with a further cartridge of 45 mm vascular stapler.
At his point the left liver remains attached only by the left hepatic vein: division of the triangular ligament was performed using monopolar hook and the hepatic vein isolated and the divided using vascular stapler.
Haemostatis was refined by application of argon beam coagulation and no bleeding was revealed even after removal of the vascular clamp (total Pringle s time 27 minutes).
Postoperative course was uneventful, minimal elevation of the liver function tests was recorded in post-operative day 1 but returned to normal at discharged on post-operative day 3.

Measuring fruit morphology and color traits of vegetable and fruit crops in an objective and reproducible way is important for detailed phenotypic analyses of these traits. Tomato Analyzer (TA) is a software program that measures 37 attributes related to two-dimensional shape in a semi-automatic and reproducible manner1,2. Many of these attributes, such as angles at the distal and proximal ends of the fruit and areas of indentation, are difficult to quantify manually. The attributes are organized in ten categories within the software: Basic Measurement, Fruit Shape Index, Blockiness, Homogeneity, Proximal Fruit End Shape, Distal Fruit End Shape, Asymmetry, Internal Eccentricity, Latitudinal Section and Morphometrics. The last category requires neither prior knowledge nor predetermined notions of the shape attributes, so morphometric analysis offers an unbiased option that may be better adapted to high-throughput analyses than attribute analysis. TA also offers the Color Test application that was designed to collect color measurements from scanned images and allow scanning devices to be calibrated using color standards3.
TA provides several options to export and analyze shape attribute, morphometric, and color data. The data may be exported to an excel file in batch mode (more than 100 images at one time) or exported as individual images. The user can choose between output that displays the average for each attribute for the objects in each image (including standard deviation), or an output that displays the attribute values for each object on the image. TA has been a valuable and effective tool for indentifying and confirming tomato fruit shape Quantitative Trait Loci (QTL), as well as performing in-depth analyses of the effect of key fruit shape genes on plant morphology. Also, TA can be used to objectively classify fruit into various shape categories. Lastly, fruit shape and color traits in other plant species as well as other plant organs such as leaves and seeds can be evaluated with TA.

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